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利用初始配药模式预测依从性轨迹。

Predicting adherence trajectory using initial patterns of medication filling.

作者信息

Franklin Jessica M, Krumme Alexis A, Shrank William H, Matlin Olga S, Brennan Troyen A, Choudhry Niteesh K

机构信息

1620 Tremont St, Ste 3030, Boston, MA 02120. E-mail:

出版信息

Am J Manag Care. 2015 Sep 1;21(9):e537-44.

PMID:26618441
Abstract

OBJECTIVES

To evaluate the ability of initial medication dispensings to predict long-term patterns of adherence.

STUDY DESIGN

A retrospective cohort study of statin initiators enrolled in a Medicare Part D drug plan from CVS Caremark from 2005 to 2008.

METHODS

We used group-based trajectory models to classify patients into 6 adherence trajectories based on patterns of statin filling over the year following therapy initiation. Baseline clinical characteristics and indicators of statin filling during the first 2 to 4 months following initiation were used to predict adherence trajectory in logistic regression models, separately within strata of the days' supply of the initial statin dispensing. Cross-validation was used to measure predictive accuracy of models in data not used for model estimation.

RESULTS

Among 77,703 statin initiators, prediction using baseline variables only was poor (cross-validated C statistic ≤ 0.61). When using 3 months of initial adherence to predict trajectory, prediction was greatly improved among patients with an index supply ≤30 days (0.62 ≤ C ≤ 0.91). With 4 months of initial adherence in the model, prediction was strong for all patients (C ≥ 0.72), especially for the best and worst trajectories (C = 0.90 and 0.94, respectively, in patients with an index supply ≤ 30 days; and C = 0.83 and 0.90, respectively, in patients with an index supply > 30 days).

CONCLUSIONS

Initial filling behavior strongly predicted future adherence trajectory. Predicting adherence trajectories may facilitate better targeting of interventions to patients most likely to benefit.

摘要

目的

评估初始药物配药预测长期依从模式的能力。

研究设计

一项对2005年至2008年参加CVS Caremark医疗保险D部分药物计划的他汀类药物起始使用者的回顾性队列研究。

方法

我们使用基于组的轨迹模型,根据治疗开始后一年中他汀类药物的配药模式,将患者分为6种依从轨迹。在逻辑回归模型中,使用基线临床特征和起始后最初2至4个月内他汀类药物配药指标来预测依从轨迹,分别在初始他汀类药物配药供应天数的各层内进行。交叉验证用于测量模型在未用于模型估计的数据中的预测准确性。

结果

在77703名他汀类药物起始使用者中,仅使用基线变量进行预测效果较差(交叉验证C统计量≤0.61)。当使用最初3个月的依从性来预测轨迹时,对于索引供应量≤30天的患者,预测有了很大改善(0.62≤C≤0.91)。模型中纳入最初4个月的依从性后,对所有患者的预测都很强(C≥0.72),尤其是对于最佳和最差轨迹(索引供应量≤30天的患者中C分别为0.90和0.94;索引供应量>30天的患者中C分别为0.83和0.90)。

结论

初始配药行为强烈预测未来的依从轨迹。预测依从轨迹可能有助于更好地将干预措施针对最可能受益的患者。

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